Association between DSM-5 and ICD-11 personality dimensional traits in a general medical cohort and readmission and mortality

被引:6
|
作者
Barroilhet, Sergio A. [1 ,2 ,3 ,4 ]
Bieling, Alexandra E. [1 ,2 ]
McCoy, Thomas H., Jr. [1 ,2 ,3 ]
Perlis, Roy H. [1 ,2 ,3 ]
机构
[1] Massachusetts Gen Hosp, Div Clin Res, Ctr Quantitat Hlth, Boston, MA 02114 USA
[2] Massachusetts Gen Hosp, Ctr Genom Med, Boston, MA 02114 USA
[3] Harvard Univ, Harvard Med Sch, Dept Psychiat, Boston, MA 02115 USA
[4] Univ Chile Clin Hosp, Univ Psychiat Clin, Santiago, Chile
关键词
Personality disorder; Personality domains; Natural language processing; Machine learning; Electronic health record; Mortality; Readmission; HEALTH-CARE UTILIZATION; PHYSICAL HEALTH; DISORDER; MODEL; BEHAVIORS; RISK; PSYCHOPATHOLOGY; COMORBIDITY; IMPULSIVITY; PREVALENCE;
D O I
10.1016/j.genhosppsych.2020.01.003
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
Background: Personality has long been studied as a factor associated with health outcomes. Investigations of large, generalizable clinical cohorts are limited by variations in personality diagnostic methodologies and difficulties with long-term follow-up. Methods: Electronic health records of a cohort of patients admitted to a general hospital were characterized using a previously developed natural language processing tool for extracting DSM-5 and ICD-11 personality domains. We used Cox regression and Fine-Gray competing risk survival to analyze the relationships between these personality estimates, sociodemographic features, and risk of readmission and mortality. Results: Among 12,274 patients, 2379 deaths occurred in the course of 61,761 patient-years at risk, with 19,985 admissions during follow-up. Detachment was the most common personality feature. Presence of disinhibition was independently associated with a higher mortality risk, while anankastic traits were associated with a lower mortality risk. Increased likelihood of readmission was predicted by detachment, while decreased likelihood of readmission was associated with disinhibition and psychoticism traits. Conclusions: Personality features can be identified from electronic health records and are associated with readmission and mortality risk. Developing treatment strategies that target patients with higher personality symptom burden in specific dimensions could enable more efficient and focused interventions.
引用
收藏
页码:63 / 67
页数:5
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